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NVIDIA

Designs the chips and software that power AI

Post-Silicon Bring-Up Senior Manager

Hardware Validation & TestingUpdated on Oct 31
Full-timeIn-person

About the Job

Requirements

  • A Bachelor of Science or Master of Science in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
  • At least 12 years of overall experience and 5 years of management experience, including significant leadership in post-silicon bring-up, validation, debug, or productization for complex systems-on-chip, GPUs, ASICs, or systems.
  • Proven experience leading teams through first-silicon bring-up, issue triage, debug closure, and transition to production.
  • Deep technical understanding of digital design, computer or system architecture, power, timing, clocking, reset, noise, fault analysis, and hardware-software interactions.
  • Strong experience with post-silicon debug and validation flows, including lab execution, test planning, data-driven issue management, and multifunctional execution.
  • Familiarity with driving silicon characterization and reliability qualification, including electrical and process-voltage-temperature characterization, HTOL, ELFR, package qualification, and AEC-Q100 for automotive programs where applicable.
  • Demonstrated ability to work effectively across pre-silicon and post-silicon teams, influence senior partners, and drive decisions across organizational boundaries.
  • Strong communication and interpersonal skills, with the ability to simplify uncertainty, create structure, and keep teams aligned under aggressive schedules.

Responsibilities

  • Lead the end-to-end post-silicon execution plan, from first-silicon power-on through production qualification and volume ramp.
  • Drive technical and program execution across architecture, design, verification, firmware, software, boards, systems, test, product engineering, and operations to achieve bring-up, debug, validation, and productization goals.
  • Lead the bring-up operating model, including priorities, staffing, customer concern paths, execution reviews, issue triage, metrics, and closure plans for the highest-risk silicon issues.
  • Lead resolution of sophisticated post-silicon issues involving power, clocks, reset, boot, interfaces, performance, reliability, and coordination between hardware components and software systems, ensuring rapid root-cause analysis and effective cross-team closure.
  • Drive silicon characterization and reliability qualification plans through execution, including assessments of electrical, speed, power, thermal, environmental, and operational conditions; customer sampling; production-release criteria; and automotive qualification flows such as AEC-Q100 when applicable.
  • Establish and continuously improve bring-up methodology, test planning, debug readiness, lab readiness, and execution processes to increase speed, quality, and predictability across programs.
  • Partner with senior leadership to communicate readiness, risks, dependencies, and recovery plans, and drive decisions that balance schedule, quality, and production objectives.
  • Help shape the broader post-silicon roadmap by applying bring-up findings to design, verification, debug architecture, and productization flows.

Desired Qualifications

  • Experience leading bring-up for both systems-on-chip- and GPU-class silicon or highly integrated platform programs.
  • Hands-on experience with first power-on, system bring-up, silicon characterization, binning, reliability qualification, or production ramp.
  • Experience building bring-up methodologies, debug infrastructure, or validation frameworks that improved execution quality across multiple product generations.
  • Strong background in firmware, low-level software, or hardware-software co-debug for complex systems.
  • Experience driving pre-silicon execution, including multifunctional planning and execution through design, verification, and tapeout readiness.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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